code: def _central_crop(image, crop_height, crop_width):
      """Performs central crops of the given image list.
  
      Args:
        image: a 3-D image tensor
        crop_height: the height of the image following the crop.
        crop_width: the width of the image following the crop.
  
      Returns:
        3-D tensor with cropped image.
      """
      shape = tf.shape(input=image)
      height, width = shape[0], shape[1]
  
      amount_to_be_cropped_h = height - crop_height
      crop_top = amount_to_be_cropped_h // 2
      amount_to_be_cropped_w = width - crop_width
      crop_left = amount_to_be_cropped_w // 2
      return tf.slice(
          image, [crop_top, crop_left, 0], [crop_height, crop_width, -1]
      )
  
file_path: autodist/examples/benchmark/utils/imagenet_preprocessing.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import os
  from absl import logging
  import tensorflow
label_desc: Use image node_id 7 for calling a global function with example usage: _central_crop(image, crop_height, crop_width) and returns: tf